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Modeling struvite precipitation in a batch reactor using a population balance model in a 3-D computational fluid dynamic (CFD) framework

Title:

Modeling struvite precipitation in a batch reactor using a population balance model in a 3-D computational fluid dynamic (CFD) framework

Mousavi, Seyyed Ebrahim (2017) Modeling struvite precipitation in a batch reactor using a population balance model in a 3-D computational fluid dynamic (CFD) framework. Masters thesis, Concordia University.

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Abstract

Discharge of significant amounts of phosphate from nutrient-rich wastewater is problematic considering the potential risk for contamination of groundwater and eutrophication of recipient water bodies. On the other hand, phosphorus is a limited, non-renewable resource with total reserves that may be depleted in the near future. As a result, phosphorus recovery is receiving increased attention as an environmental concern. The recovery of phosphorus using a precipitation technique is one proven solution for this issue. In this work, the precipitation of Magnesium Ammonium Phosphate (Struvite) as an alternative method for the recovery of phosphorous is modeled in a batch stirred tank reactor. The aim of this work is to link Computational Fluid Dynamics (CFD) with Population Balance Modeling (PBM) to develop a 3-D CFD model that can predict the Crystal Size Distribution (CSD) of struvite. In the simulation, the CFD flow field was solved through a Eulerian multiphase approach and RNG k-ɛ turbulence model, using a commercial CFD package, ANSYS Fluent 17.1. The population balance equation was solved using the discrete method, implementing 25 different size classes. The size-independent growth rate as a function of the supersaturation index (SI) was employed in the model through User Defined Function (UDF). A series of experiments were conducted utilizing synthetic wastewater in a stirred tank reactor agitated with a Rushton impeller to confirm the simulation results. The model successfully predicted the variation in crystal size distribution as well as SI values over the experiment time period.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (Masters)
Authors:Mousavi, Seyyed Ebrahim
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Civil Engineering
Date:30 March 2017
Thesis Supervisor(s):Rahaman, Md. Saifur
ID Code:982370
Deposited By: SEYYED EBRAHIM MOUSAVI
Deposited On:09 Jun 2017 13:58
Last Modified:31 Jul 2018 00:00
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